Author: Ari Yeganeh https://www.linkedin.com/in/ariyeg/
This an exploratory analysis on:
What are the global employment trends and how is Australia, the lucky country, faring compared to it's OECD counterparts?
Let's dive in.
# Let's load our required libraries
import pandas as pd
import plotly.express as px
import plotly.io as pio
pio.renderers.default = "notebook"
Firstly we need to download our datasets. I'm using OECD's employment database found here: https://www.oecd.org/employment/onlineoecdemploymentdatabase.htm
# Read data from file downloaded from OECD database: https://www.oecd.org/employment/onlineoecdemploymentdatabase.htm
data = pd.read_csv("LFS_SEXAGE_I_R_12042021073636427.csv")
# Preview the first 5 lines of the loaded data
data.head(3)
| COUNTRY | Country | SEX | Sex | AGE | Age | SERIES | Series | FREQ | Frequency | ... | Time | Unit Code | Unit | PowerCode Code | PowerCode | Reference Period Code | Reference Period | Value | Flag Codes | Flags | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | AUS | Australia | MW | All persons | 1519 | 15 to 19 | EPR | Employment/population ratio | A | Annual | ... | 2000 | PC | Percentage | 0 | Units | NaN | NaN | 49.215684 | NaN | NaN |
| 1 | AUS | Australia | MW | All persons | 1519 | 15 to 19 | EPR | Employment/population ratio | A | Annual | ... | 2001 | PC | Percentage | 0 | Units | NaN | NaN | 49.416769 | NaN | NaN |
| 2 | AUS | Australia | MW | All persons | 1519 | 15 to 19 | EPR | Employment/population ratio | A | Annual | ... | 2002 | PC | Percentage | 0 | Units | NaN | NaN | 49.012172 | NaN | NaN |
3 rows × 21 columns
data.info()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 178844 entries, 0 to 178843 Data columns (total 21 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 COUNTRY 178844 non-null object 1 Country 178844 non-null object 2 SEX 178844 non-null object 3 Sex 178844 non-null object 4 AGE 178844 non-null int64 5 Age 178844 non-null object 6 SERIES 178844 non-null object 7 Series 178844 non-null object 8 FREQ 178844 non-null object 9 Frequency 178844 non-null object 10 TIME 178844 non-null int64 11 Time 178844 non-null int64 12 Unit Code 178844 non-null object 13 Unit 178844 non-null object 14 PowerCode Code 178844 non-null int64 15 PowerCode 178844 non-null object 16 Reference Period Code 0 non-null float64 17 Reference Period 0 non-null float64 18 Value 178844 non-null float64 19 Flag Codes 0 non-null float64 20 Flags 0 non-null float64 dtypes: float64(5), int64(4), object(12) memory usage: 28.7+ MB
We note here, there are a number of missing values in our dataset, however as these pertain to reference codes and flags, we will ignore for the time being.
To add further insights to our analysis let's import the gapminder dataset
# Bring in continent information from gapminder dataset
gapminder = px.data.gapminder().drop_duplicates(['country','continent'])
country_iso = gapminder[['country','continent']]
data = pd.merge(data, country_iso,how='left', left_on='Country',right_on='country')
Now let's look at high level unemployment rates for different countries in the OECD...
df = data[(data.Sex == 'All persons') & (data.Age=='Total') & (data.Series== 'Unemployment rate')]
chart_df = df.query("Time == 2019")
chart_df = chart_df[chart_df['continent'].notna()]
#chart_df.head()
fig = px.treemap(chart_df, path=[px.Constant('world'), 'continent', 'Country'], values='Value',
color='Value', hover_data=['Country'])
fig.update_layout(autosize=True, showlegend=True,
title= "Unemployment rate in OECD nations (2019)", template="simple_white")
fig.show()
Comparing broadly to the rest of OECD nations, Australia's unemployment pales in comparison to Latin American nations, South Africa and some European nations.
Note: the above chart is NOT additive. i.e. continent level or world level data cannot be used as it's simply the sum unemployment in the respective groups.
fig = px.choropleth(df, locations="COUNTRY", color="Value", hover_name="Country", animation_frame="Time", range_color=[0,30])
fig.update_layout(autosize=True, showlegend=True,
title= "Unemployment rate in OECD nations over time", template="simple_white")
fig.show()
Over time we can see some inconsistencies in our data with nations like India and China appearing in some years but not others. Also we note, the relative large differences in unemployment across nations over time.
Let's now look at Australia and comparable countries more specifically:
# Create subset dataset for Unemployment rate for select OECD countries
df = data[(data.Sex == 'All persons') & (data.Age=='Total') & (data.Series== 'Unemployment rate')]
countries_list = ['Australia', 'New Zealand', 'United States', 'OECD countries', 'United Kingdom']
unemployment = df[df['Country'].isin(countries_list)]
unemployment = unemployment[["Country", "Time", "Value"]]
# Plot unemployment by country over the last 20 years
fig = px.line(unemployment, x="Time", y="Value", color='Country',
labels={
"Value":"Unemployment rate %",
"Time": "Year"
},
title = "Unemployment rate by select countries")
fig.update_layout(autosize=True, showlegend=True, template="simple_white")
fig.update_yaxes(range=[0, 10])
fig.show()
Australia had a relatively low unemployment rate relative to other developed countries. However since 2015, it has fallen behind it's counterparts lagging a full percentage point behind by 2019.
# Explore differences in age and gender
df_age = data
countries_list = ['Australia', 'New Zealand', 'United States', 'OECD countries', 'United Kingdom']
age_list = ['15 to 24', '25 to 34', '35 to 44', '45 to 54', '55 to 64', '65+']
df_age = df_age[df_age['Country'].isin(countries_list)]
df_age = df_age[df_age['Age'].isin(age_list)]
df_age = df_age[["Country", "Time", "Value", "Age", "Sex", "Series"]]
df_age_gender = df_age[(df_age.Sex != 'All persons') ]
df_age = df_age[(df_age.Sex == 'All persons') ]
# unemployment_age.head()
# Plot unemployment by age in Australia
fig = px.scatter(df_age[(df_age.Country =='Australia') & (df_age.Series== 'Unemployment rate')], x="Time", y="Value", color='Age',
labels={
"Value":"Unemployment rate %",
"Time": "Year"
},
title = "Unemployment rate by Age in Australia", size = "Value")
fig.update_layout(autosize=True, showlegend=True, template="simple_white")
fig.show()
In Australia, we can observe a large difference in unemployment by age groups; with younger demographics experiencing an unemployment rate of upto twice as the rest of adult population.
The difference is particularly apparent straight after the 2008 global financial crisis with 15-24 year olds experiencing an almost 50% increase in unemployment rate in just one year.
# Plot Participation rate by age and gender in Australia
fig = px.line(df_age_gender[(df_age_gender.Country =='Australia') & (df_age_gender.Series== 'Labour force participation rate')], x="Time", y="Value", color='Age',
facet_col="Sex",
labels={
"Value":"Labour force participation rate %",
"Time": "Year"
},
title = "Labour force participation rate by Age and Gender in Australia")
fig.update_layout(autosize=True, showlegend=True, template="simple_white")
fig.show()
The labour force participation rates measures the economy's active workforce. It is calculated as the labour force divided by the total working-age population.
In Australia, we can see a large differences by gender and age. Specifically, we can see much higher rates of participation for men and the age groups 25-45.
We can also observe siginifcant changes for female in the age group 55-64 from 35% participation in 2000, to over 61% in 2019. This pattern is consistent across older age groups for both genders signalling a return to the workforce from this older age groups.
Interestingly, men over 65 had double the participation of women in the same age group. Whilst the difference in younger age groups can be partly explained by the impact of child bearing for women, at age 65, there seems to be other factors at play.
Now let's look at participation rates across select countries...
# Observe Labour force participation by gender
df = data[(data.Sex !='All persons' ) & (data.Age=='Total') & (data.SERIES== 'LFPR')]
countries_list = ['Australia', 'New Zealand', 'United States', 'OECD countries', 'United Kingdom']
df_filtered = df[df['Country'].isin(countries_list)]
df_labour = df_filtered[["Country", "Time", "Sex", "Value"]]
fig = px.line(df_labour, x="Time", y="Value", color='Country', facet_col="Sex",
labels={
"Value":"Labour Participation rate %",
"Time": "Year"
},
title = "Labour Participation rate by Country & Gender")
fig.update_yaxes(range=(40, 90))
fig.update_layout(autosize=True, showlegend=True, template="simple_white")
fig.show()
The above chart chart shows the large gap between men and women participation rates. It's clear there a significant difference in participation rate by both gender and country.
Let's look at this difference more closely...
# df_labour.head()
df_labour_p = pd.pivot_table(df_labour, index = ['Country','Time'], columns='Sex', values = 'Value').reset_index()
df_labour_p['Diff_LP'] = df_labour_p.Men - df_labour_p.Women
df_labour_p.head()
fig = px.line(df_labour_p, x="Time", y="Diff_LP", color='Country',
labels={
"Diff_LP":"Difference (Men - Women Participation) %",
"Time": "Year"
},
title = "Difference between Men and Women Labour Participation rate by Country")
fig.update_layout(autosize=True, showlegend=True, template="simple_white")
fig.show()
The difference between Men and Women participation rates in the workforce seems to be reducing amongst all developed countries with OECD countries reducing the gap from 22% to 16% from 2000-2019.
New Zealand had the lowest difference in participation rates amongst developed nations with a rate almost half of the OECD average. Australia and UK are not far behind, however the US seems to be going backwards in this trend, indicating a larger differences in employment outcomes between the genders.
Let's now explore skill shortages across Australia and other OECD nations.
First, let's download and clean up the data from: https://stats.oecd.org/Index.aspx?QueryId=64196#
# Read data from file downloaded from OECD database: https://stats.oecd.org/Index.aspx?QueryId=64196#
df_skills = pd.read_csv("SKILLS_2018_INDUSTRY_14042021065332796.csv")
df_skills_cntry = pd.read_csv("SKILLS_2018_TOTAL_14042021073027206.csv")
countries_list = ['Australia', 'New Zealand', 'United States', 'OECD - Total', 'United Kingdom', 'Germany', 'France']
df_skills = df_skills[df_skills['Country'].isin(countries_list)]
df_skills = df_skills[["Country", "Industry", "Value", "Type", "Skills"]]
df_skills_cntry = df_skills_cntry[df_skills_cntry['Country'].isin(countries_list)]
df_skills_cntry = df_skills_cntry[["Country", "Value", "Type", "Skills"]]
Let's have a look at overall skills shortages across select countries
chart_df = df_skills_cntry.groupby(["Country","Type"])["Value"].sum().reset_index()
fig = px.scatter(chart_df, x="Country", y="Value", color='Type', size = abs(chart_df.Value) ,
labels={
"Value":"Skill Shortage (Higher value = higher shortage)"
},
title = "Skills Shortage for select countries")
fig.update_layout(autosize=True, showlegend=True, template="simple_white")
fig.show()
We can see large differences in skills gaps across these select countries. We might want to explore further the meanings behind each classification by refering the documentation here from the OECD: https://www.oecd.org/els/emp/OECD%20Skills%20for%20Jobs%20Definitions.pdf
For now, let's look more specifically into the types of skills that make up each broad group.
df_au = df_skills_cntry[(df_skills_cntry.Country=='Australia')]
#df_au.Value.astype(float).head()
pd.options.mode.chained_assignment = None
df_au['Value_1'] = df_au.Value + 1
fig = px.treemap(df_au, path=['Type', 'Skills'],
values="Value_1", color_continuous_scale='RdBu_r',
color= "Value_1", hover_data=['Skills']
, labels={
"Value_1":"Skill Shortage"
},
)
fig.update_layout(autosize=True, showlegend=True,
title= "Overview of Skills Shortages in Australia (Higher Value = Higher Skills Shortage)"
, template="simple_white")
fig.show()
The above chart gives us a better understanding of what types of skills are under each broad skill group. Hover over tiles to see more information about the skill group and extent of shortage/surplus. From this, we can start to see clear skills gaps in Workstyles and Knowledge in Australia. Specifically, there are large shortages in:
Further, we note skills on the other side of the spectrum with lower shortages and even surplus:
Let's now look at the industries most affected by these skills shortages.
# truncate industries as they don't fit on graph
df_skills["Industry"] = df_skills["Industry"].str[:30]
df_au = df_skills[(df_skills.Country =='Australia')].groupby('Industry')['Value'].sum()\
.reset_index().sort_values(by='Value')
fig = px.scatter(df_au, x="Industry", y="Value", color='Industry',
size = abs(df_au.Value),
labels={
"Value":"Skill Shortage (Higher value = higher shortage)"
},
title = "Skills Shortage by Industry in Australia (red=shortage, green=surplus)")
fig.update_layout(autosize=True, showlegend=True, template="simple_white")
# add a red and green box indicating skill shortage or surplus
fig.add_hrect(
y0=df_au.Value.min()-5, y1="0",
fillcolor="Green", opacity=0.1,
layer="below", line_width=0,
)
fig.add_hrect(
y0="0", y1=df_au.Value.max()+5,
fillcolor="Red", opacity=0.1,
layer="below", line_width=0,
)
fig.show()
In Australia, we can see industries with largest skills gaps on the right of the chart with Education and Human Health & Social Work topping the list. On the other side of the chart, we have industries in skill surplus: Wholesale and Retail Trade and Accomodation & Food Services.
Let's see how these numbers compare against select countries...
df_au = df_skills.groupby(['Country','Industry'])['Value'].sum()\
.reset_index().sort_values(by='Value')
fig = px.scatter(df_au, x="Country", y="Value", color='Industry',
size = abs(df_au.Value),
labels={
"Value":"Skill Shortage (Higher value = higher shortage)"
},
title = "Skills Shortage for Select Countries (red=shortage, green=surplus)")
fig.update_layout(autosize=True, showlegend=True, template="simple_white")
# add a red and green box indicating skill shortage or surplus
fig.add_hrect(
y0=df_au.Value.min()-5, y1="0",
fillcolor="Green", opacity=0.1,
layer="below", line_width=0,
)
fig.add_hrect(
y0="0", y1=df_au.Value.max()+5,
fillcolor="Red", opacity=0.1,
layer="below", line_width=0,
)
fig.show()
It seems Australia is not alone in it's shortage of Education sector skills with this sector being OECD's top industry for skills shortages by a large margin.
Interestingly, industries with a surplus e.g. "Human Health & Social Work" in other countries like Germany are the same industries Australia has a large shortage in. This type of data might be useful to inform skilled migration strategies between nations.
Now let's look at Australia's skills outlook in more detail by the type of skills within each industry...
df_au = df_skills[(df_skills.Country =='Australia')]
ct = pd.crosstab(df_au.Skills, df_au.Industry, aggfunc='sum', values=df_au.Value).\
style.background_gradient(cmap='RdYlGn_r')
ct.format('{:.2f}')
| Industry | Accomodation and Food Service | Agriculture, Forestry and Fish | Arts, Entertainment and Recrea | Construction | Education | Electricity, Gas, Steam and Ai | Financial and Insurance Activi | Human Health and Social Work A | Information and Communication | Manufacturing | Mining and Quarrying | Other Service Activities | Public Administration and Defe | Real Estate Activities | Transportation and Storage | Wholesale and Retail Trade; Re |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Skills | ||||||||||||||||
| Achievement Orientation | -0.17 | 0.20 | -0.06 | 0.17 | 0.61 | 0.04 | -0.07 | 0.38 | -0.09 | -0.15 | -0.06 | -0.02 | -0.07 | -0.05 | -0.05 | -0.23 |
| Achievement/Effort | -0.17 | 0.17 | -0.07 | 0.15 | 0.58 | 0.04 | -0.07 | 0.34 | -0.08 | -0.15 | -0.06 | -0.03 | -0.06 | -0.04 | -0.05 | -0.23 |
| Active Learning | -0.05 | 0.09 | -0.01 | 0.07 | 0.28 | 0.03 | -0.02 | 0.18 | -0.04 | -0.04 | 0.00 | 0.00 | -0.02 | -0.02 | -0.01 | -0.06 |
| Active Listening | -0.08 | 0.12 | -0.02 | 0.08 | 0.34 | 0.02 | -0.04 | 0.22 | -0.05 | -0.06 | -0.01 | -0.00 | -0.04 | -0.03 | -0.01 | -0.10 |
| Adaptability/Flexibility | -0.19 | 0.18 | -0.07 | 0.16 | 0.67 | 0.04 | -0.08 | 0.45 | -0.09 | -0.16 | -0.07 | -0.02 | -0.08 | -0.05 | -0.05 | -0.24 |
| Adjustment | -0.21 | 0.18 | -0.08 | 0.16 | 0.67 | 0.04 | -0.08 | 0.46 | -0.08 | -0.16 | -0.07 | -0.02 | -0.09 | -0.06 | -0.05 | -0.27 |
| Administration and Management | -0.06 | 0.16 | -0.01 | 0.09 | 0.20 | 0.03 | -0.02 | 0.10 | -0.03 | -0.04 | -0.01 | -0.01 | -0.02 | -0.01 | -0.01 | -0.06 |
| Analytical Thinking | -0.13 | 0.19 | -0.04 | 0.19 | 0.56 | 0.06 | -0.07 | 0.38 | -0.10 | -0.11 | -0.03 | -0.01 | -0.05 | -0.04 | -0.03 | -0.17 |
| Arm-Hand Steadiness | -0.06 | 0.08 | -0.04 | 0.09 | 0.05 | 0.03 | -0.02 | 0.10 | -0.01 | -0.07 | -0.06 | -0.02 | -0.02 | -0.01 | -0.01 | -0.08 |
| Arts and Humanities | -0.01 | 0.01 | 0.01 | 0.01 | 0.14 | 0.00 | 0.00 | 0.05 | -0.00 | -0.00 | 0.01 | 0.01 | 0.00 | -0.00 | -0.00 | -0.00 |
| Attention to Detail | -0.22 | 0.21 | -0.08 | 0.21 | 0.63 | 0.05 | -0.11 | 0.45 | -0.10 | -0.21 | -0.11 | -0.04 | -0.10 | -0.06 | -0.06 | -0.28 |
| Attentiveness | -0.06 | 0.08 | -0.02 | 0.06 | 0.20 | 0.02 | -0.02 | 0.13 | -0.02 | -0.05 | -0.03 | -0.01 | -0.03 | -0.01 | -0.00 | -0.07 |
| Auditory Attention | -0.03 | 0.08 | -0.01 | 0.06 | 0.11 | 0.02 | -0.01 | 0.09 | -0.01 | -0.05 | -0.04 | -0.00 | -0.02 | -0.01 | 0.00 | -0.05 |
| Auditory and Speech Abilities | -0.05 | 0.07 | -0.02 | 0.05 | 0.17 | 0.02 | -0.02 | 0.12 | -0.02 | -0.05 | -0.02 | -0.00 | -0.03 | -0.01 | -0.00 | -0.07 |
| Basic Skills (Content) | -0.05 | 0.09 | -0.01 | 0.06 | 0.26 | 0.02 | -0.03 | 0.17 | -0.04 | -0.04 | 0.00 | -0.00 | -0.02 | -0.02 | -0.01 | -0.07 |
| Basic Skills (Process) | -0.06 | 0.10 | -0.01 | 0.08 | 0.32 | 0.03 | -0.03 | 0.20 | -0.04 | -0.05 | -0.01 | 0.00 | -0.03 | -0.02 | -0.01 | -0.07 |
| Biology | -0.01 | 0.13 | 0.00 | 0.01 | 0.09 | 0.00 | 0.00 | 0.14 | -0.00 | -0.00 | 0.03 | 0.01 | 0.00 | -0.00 | -0.00 | 0.00 |
| Building and Construction | -0.01 | 0.08 | -0.00 | 0.20 | 0.02 | 0.07 | 0.00 | 0.01 | 0.02 | -0.00 | -0.00 | -0.00 | -0.00 | 0.01 | -0.01 | -0.02 |
| Business and Management | -0.05 | 0.09 | -0.02 | 0.05 | 0.15 | 0.01 | -0.02 | 0.09 | -0.02 | -0.03 | 0.00 | -0.01 | -0.03 | -0.02 | -0.01 | -0.07 |
| Category Flexibility | -0.06 | 0.08 | -0.02 | 0.07 | 0.24 | 0.02 | -0.03 | 0.17 | -0.04 | -0.06 | -0.02 | -0.01 | -0.02 | -0.02 | -0.02 | -0.08 |
| Chemistry | -0.03 | 0.08 | -0.01 | 0.05 | 0.07 | 0.01 | -0.00 | 0.10 | 0.00 | -0.03 | -0.01 | -0.01 | -0.00 | 0.00 | -0.01 | -0.03 |
| Clerical | -0.04 | 0.07 | -0.02 | 0.04 | 0.24 | 0.00 | -0.05 | 0.11 | -0.03 | -0.03 | 0.00 | -0.01 | -0.04 | -0.04 | -0.02 | -0.05 |
| Cognitive Abilities | -0.06 | 0.09 | -0.01 | 0.07 | 0.23 | 0.03 | -0.03 | 0.16 | -0.03 | -0.05 | -0.01 | -0.00 | -0.03 | -0.02 | -0.01 | -0.07 |
| Communications | -0.02 | 0.04 | -0.00 | 0.03 | 0.13 | 0.03 | -0.01 | 0.06 | -0.02 | -0.01 | 0.01 | 0.00 | -0.01 | -0.01 | 0.00 | -0.03 |
| Communications and Media | -0.03 | 0.03 | 0.00 | 0.02 | 0.20 | 0.01 | -0.01 | 0.08 | -0.02 | -0.01 | 0.01 | 0.01 | -0.01 | -0.01 | -0.00 | -0.03 |
| Complex Problem Solving | -0.05 | 0.10 | -0.01 | 0.07 | 0.24 | 0.03 | -0.02 | 0.17 | -0.04 | -0.04 | -0.01 | 0.00 | -0.02 | -0.01 | -0.01 | -0.06 |
| Complex Problem Solving Skills | -0.05 | 0.10 | -0.01 | 0.07 | 0.24 | 0.03 | -0.02 | 0.17 | -0.04 | -0.04 | -0.01 | 0.00 | -0.02 | -0.01 | -0.01 | -0.06 |
| Computers and Electronics | -0.04 | 0.05 | -0.01 | 0.06 | 0.27 | 0.03 | -0.04 | 0.12 | -0.10 | -0.03 | 0.01 | -0.01 | -0.03 | -0.02 | -0.01 | -0.06 |
| Concern for Others | -0.20 | 0.16 | -0.07 | 0.15 | 0.68 | 0.02 | -0.08 | 0.49 | -0.07 | -0.15 | -0.06 | -0.02 | -0.09 | -0.05 | -0.04 | -0.24 |
| Conscientiousness | -0.22 | 0.21 | -0.08 | 0.20 | 0.68 | 0.04 | -0.10 | 0.48 | -0.10 | -0.20 | -0.09 | -0.03 | -0.10 | -0.06 | -0.06 | -0.29 |
| Control Movement Abilities | -0.03 | 0.08 | -0.02 | 0.05 | 0.02 | 0.02 | -0.01 | 0.04 | 0.01 | -0.06 | -0.05 | -0.01 | -0.02 | -0.00 | 0.01 | -0.06 |
| Control Precision | -0.05 | 0.10 | -0.03 | 0.07 | 0.02 | 0.03 | -0.01 | 0.05 | -0.00 | -0.08 | -0.07 | -0.02 | -0.02 | -0.00 | 0.01 | -0.08 |
| Cooperation | -0.22 | 0.17 | -0.08 | 0.17 | 0.67 | 0.03 | -0.10 | 0.45 | -0.09 | -0.18 | -0.08 | -0.03 | -0.09 | -0.06 | -0.06 | -0.29 |
| Coordination | -0.07 | 0.12 | -0.02 | 0.08 | 0.28 | 0.02 | -0.03 | 0.18 | -0.03 | -0.06 | -0.02 | -0.00 | -0.03 | -0.02 | -0.02 | -0.09 |
| Critical Thinking | -0.07 | 0.12 | -0.02 | 0.09 | 0.31 | 0.03 | -0.04 | 0.21 | -0.05 | -0.06 | -0.01 | -0.00 | -0.03 | -0.02 | -0.01 | -0.09 |
| Customer and Personal Service | -0.14 | 0.11 | -0.06 | 0.10 | 0.33 | 0.02 | -0.05 | 0.25 | -0.05 | -0.05 | 0.02 | -0.03 | -0.06 | -0.04 | -0.02 | -0.16 |
| Deductive Reasoning | -0.07 | 0.11 | -0.02 | 0.09 | 0.31 | 0.04 | -0.03 | 0.21 | -0.04 | -0.06 | -0.01 | -0.01 | -0.03 | -0.02 | -0.01 | -0.09 |
| Dependability | -0.23 | 0.22 | -0.09 | 0.20 | 0.72 | 0.04 | -0.11 | 0.50 | -0.10 | -0.21 | -0.10 | -0.03 | -0.10 | -0.06 | -0.06 | -0.30 |
| Depth Perception | -0.03 | 0.10 | -0.02 | 0.06 | 0.03 | 0.03 | -0.00 | 0.05 | 0.00 | -0.05 | -0.04 | -0.01 | -0.02 | -0.00 | 0.01 | -0.05 |
| Design | -0.01 | 0.07 | -0.00 | 0.13 | 0.06 | 0.05 | -0.00 | 0.02 | -0.02 | -0.02 | -0.01 | -0.01 | 0.00 | 0.01 | -0.00 | -0.04 |
| Dynamic Flexibility | -0.00 | 0.00 | -0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | -0.00 | -0.00 | 0.00 | -0.00 | 0.00 | -0.00 | -0.00 |
| Dynamic Strength | -0.03 | 0.05 | -0.02 | 0.04 | 0.02 | 0.01 | -0.01 | 0.04 | 0.00 | -0.04 | -0.03 | -0.01 | -0.02 | -0.00 | -0.01 | -0.04 |
| Economics and Accounting | -0.02 | 0.06 | -0.01 | 0.03 | 0.04 | 0.00 | -0.01 | 0.04 | -0.01 | -0.01 | 0.00 | -0.01 | -0.01 | -0.01 | -0.01 | -0.03 |
| Education and Training | -0.05 | 0.11 | -0.01 | 0.09 | 0.51 | 0.03 | -0.01 | 0.24 | -0.03 | -0.04 | 0.00 | 0.01 | -0.02 | -0.01 | -0.01 | -0.06 |
| Endurance | -0.04 | 0.05 | -0.02 | 0.05 | 0.05 | 0.01 | -0.01 | 0.07 | 0.00 | -0.04 | -0.04 | -0.01 | -0.02 | -0.00 | -0.02 | -0.06 |
| Engineering and Technology | -0.02 | 0.07 | -0.01 | 0.13 | 0.09 | 0.05 | -0.01 | 0.04 | -0.02 | -0.03 | -0.01 | -0.01 | -0.01 | 0.00 | -0.01 | -0.04 |
| Engineering, Mechanics and Technology | -0.01 | 0.06 | -0.01 | 0.09 | 0.05 | 0.04 | -0.01 | 0.03 | -0.03 | -0.03 | -0.01 | -0.01 | 0.00 | 0.00 | -0.00 | -0.04 |
| Equipment Maintenance | -0.01 | 0.04 | -0.01 | 0.06 | 0.00 | 0.04 | 0.00 | 0.00 | 0.01 | -0.04 | -0.04 | -0.01 | -0.00 | 0.00 | 0.00 | -0.03 |
| Equipment Selection | -0.01 | 0.04 | -0.01 | 0.06 | 0.01 | 0.03 | -0.00 | 0.01 | -0.00 | -0.03 | -0.03 | -0.00 | -0.00 | 0.00 | -0.00 | -0.02 |
| Explosive Strength | -0.00 | 0.01 | -0.00 | 0.01 | 0.01 | 0.00 | -0.00 | 0.02 | 0.00 | -0.01 | -0.01 | 0.00 | -0.01 | -0.00 | -0.00 | -0.01 |
| Extent Flexibility | -0.05 | 0.06 | -0.03 | 0.09 | 0.03 | 0.03 | -0.01 | 0.06 | 0.01 | -0.06 | -0.05 | -0.01 | -0.02 | 0.00 | -0.02 | -0.07 |
| Far Vision | -0.05 | 0.10 | -0.02 | 0.07 | 0.21 | 0.03 | -0.02 | 0.13 | -0.02 | -0.05 | -0.02 | -0.01 | -0.04 | -0.01 | 0.01 | -0.07 |
| Fine Arts | -0.00 | 0.00 | 0.01 | 0.00 | 0.10 | 0.00 | 0.00 | 0.02 | -0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | -0.00 | -0.00 |
| Fine Manipulative Abilities | -0.06 | 0.08 | -0.04 | 0.08 | 0.06 | 0.03 | -0.02 | 0.09 | -0.01 | -0.07 | -0.06 | -0.02 | -0.02 | -0.01 | -0.02 | -0.08 |
| Finger Dexterity | -0.06 | 0.08 | -0.03 | 0.09 | 0.11 | 0.03 | -0.02 | 0.11 | -0.02 | -0.07 | -0.05 | -0.02 | -0.02 | -0.01 | -0.01 | -0.08 |
| Flexibility of Closure | -0.05 | 0.08 | -0.02 | 0.07 | 0.18 | 0.02 | -0.02 | 0.14 | -0.03 | -0.05 | -0.02 | -0.01 | -0.03 | -0.01 | -0.01 | -0.06 |
| Flexibility, Balance and Coordination | -0.03 | 0.04 | -0.01 | 0.06 | 0.02 | 0.02 | -0.00 | 0.04 | 0.01 | -0.03 | -0.03 | -0.01 | -0.01 | 0.00 | -0.01 | -0.04 |
| Fluency of Ideas | -0.05 | 0.08 | -0.01 | 0.07 | 0.26 | 0.03 | -0.01 | 0.15 | -0.04 | -0.03 | 0.00 | 0.00 | -0.01 | -0.01 | -0.01 | -0.06 |
| Food Production | -0.03 | 0.08 | -0.01 | 0.01 | 0.02 | -0.00 | -0.00 | 0.02 | -0.00 | -0.01 | -0.01 | -0.01 | -0.00 | -0.00 | -0.00 | -0.02 |
| Geography | -0.01 | 0.05 | 0.00 | 0.02 | 0.16 | 0.01 | -0.00 | 0.05 | -0.01 | -0.00 | 0.01 | 0.01 | -0.01 | -0.00 | 0.01 | -0.02 |
| Glare Sensitivity | -0.00 | 0.05 | -0.01 | 0.03 | 0.00 | 0.02 | -0.00 | 0.00 | 0.01 | -0.01 | -0.01 | -0.00 | -0.01 | 0.00 | 0.02 | -0.02 |
| Gross Body Coordination | -0.03 | 0.05 | -0.02 | 0.06 | 0.04 | 0.01 | -0.01 | 0.06 | 0.00 | -0.04 | -0.03 | -0.01 | -0.02 | -0.00 | -0.01 | -0.05 |
| Gross Body Equilibrium | -0.02 | 0.05 | -0.01 | 0.07 | 0.02 | 0.02 | -0.00 | 0.04 | 0.01 | -0.02 | -0.02 | -0.00 | -0.01 | 0.00 | -0.01 | -0.03 |
| Health Services | -0.01 | 0.02 | 0.00 | 0.01 | 0.14 | 0.00 | -0.00 | 0.21 | -0.01 | -0.00 | 0.03 | 0.01 | -0.01 | -0.01 | -0.00 | -0.00 |
| Hearing Sensitivity | -0.03 | 0.06 | -0.02 | 0.05 | 0.09 | 0.02 | -0.01 | 0.08 | -0.01 | -0.05 | -0.04 | -0.00 | -0.02 | -0.01 | 0.01 | -0.06 |
| History and Archaeology | -0.00 | 0.01 | 0.01 | 0.01 | 0.16 | 0.00 | 0.00 | 0.04 | -0.00 | 0.00 | 0.00 | 0.01 | 0.00 | -0.00 | 0.00 | -0.00 |
| Independence | -0.19 | 0.19 | -0.07 | 0.16 | 0.60 | 0.03 | -0.08 | 0.41 | -0.08 | -0.16 | -0.08 | -0.03 | -0.08 | -0.05 | -0.05 | -0.24 |
| Inductive Reasoning | -0.07 | 0.10 | -0.02 | 0.09 | 0.29 | 0.03 | -0.03 | 0.22 | -0.04 | -0.05 | -0.01 | -0.00 | -0.03 | -0.02 | -0.01 | -0.08 |
| Information Ordering | -0.07 | 0.09 | -0.02 | 0.09 | 0.27 | 0.03 | -0.04 | 0.19 | -0.04 | -0.07 | -0.02 | -0.01 | -0.03 | -0.02 | -0.01 | -0.09 |
| Initiative | -0.17 | 0.22 | -0.06 | 0.18 | 0.64 | 0.05 | -0.07 | 0.42 | -0.09 | -0.16 | -0.07 | -0.02 | -0.07 | -0.05 | -0.05 | -0.23 |
| Innovation | -0.13 | 0.18 | -0.04 | 0.17 | 0.57 | 0.04 | -0.06 | 0.35 | -0.08 | -0.12 | -0.05 | -0.01 | -0.05 | -0.03 | -0.03 | -0.17 |
| Installation | -0.00 | -0.00 | -0.00 | 0.06 | 0.00 | 0.04 | 0.00 | 0.00 | 0.00 | -0.00 | -0.00 | -0.00 | 0.00 | 0.00 | -0.00 | -0.01 |
| Instructing | -0.05 | 0.09 | -0.01 | 0.07 | 0.33 | 0.02 | -0.02 | 0.18 | -0.03 | -0.04 | -0.01 | 0.00 | -0.02 | -0.01 | -0.01 | -0.06 |
| Integrity | -0.22 | 0.20 | -0.08 | 0.18 | 0.71 | 0.04 | -0.10 | 0.49 | -0.10 | -0.18 | -0.07 | -0.03 | -0.10 | -0.07 | -0.06 | -0.29 |
| Interpersonal Orientation | -0.20 | 0.16 | -0.07 | 0.15 | 0.66 | 0.02 | -0.08 | 0.45 | -0.07 | -0.15 | -0.06 | -0.02 | -0.08 | -0.05 | -0.05 | -0.25 |
| Judgment and Decision Making | -0.06 | 0.10 | -0.01 | 0.08 | 0.28 | 0.03 | -0.02 | 0.18 | -0.04 | -0.05 | -0.01 | -0.00 | -0.02 | -0.02 | -0.01 | -0.07 |
| Law and Government | -0.02 | 0.06 | -0.00 | 0.04 | 0.15 | 0.01 | -0.01 | 0.09 | -0.01 | -0.01 | 0.01 | 0.01 | -0.03 | -0.01 | 0.00 | -0.03 |
| Law and Public Safety | -0.04 | 0.06 | -0.01 | 0.07 | 0.15 | 0.02 | -0.01 | 0.10 | -0.01 | -0.02 | 0.00 | -0.00 | -0.04 | -0.01 | 0.00 | -0.05 |
| Leadership | -0.14 | 0.22 | -0.05 | 0.20 | 0.62 | 0.05 | -0.06 | 0.38 | -0.06 | -0.12 | -0.05 | -0.01 | -0.07 | -0.04 | -0.05 | -0.19 |
| Learning Strategies | -0.04 | 0.09 | -0.00 | 0.07 | 0.36 | 0.03 | -0.02 | 0.18 | -0.02 | -0.03 | 0.00 | 0.01 | -0.02 | -0.01 | -0.00 | -0.05 |
| Management of Financial Resources | -0.01 | 0.07 | -0.00 | 0.03 | 0.03 | 0.02 | -0.00 | 0.03 | -0.01 | -0.00 | 0.01 | -0.00 | -0.00 | -0.00 | 0.01 | -0.01 |
| Management of Material Resources | -0.02 | 0.07 | -0.00 | 0.04 | 0.06 | 0.02 | -0.01 | 0.04 | -0.01 | -0.01 | 0.00 | -0.00 | -0.00 | -0.00 | 0.00 | -0.02 |
| Management of Personnel Resources | -0.04 | 0.13 | -0.01 | 0.07 | 0.18 | 0.03 | -0.01 | 0.11 | -0.02 | -0.03 | -0.00 | -0.00 | -0.02 | -0.01 | -0.01 | -0.05 |
| Manual Dexterity | -0.06 | 0.08 | -0.04 | 0.08 | 0.04 | 0.03 | -0.02 | 0.07 | -0.00 | -0.08 | -0.07 | -0.02 | -0.02 | -0.01 | -0.02 | -0.08 |
| Manufacturing and Production | -0.03 | 0.08 | -0.01 | 0.03 | 0.03 | 0.00 | -0.01 | 0.03 | -0.00 | -0.04 | -0.04 | -0.01 | -0.00 | -0.00 | -0.01 | -0.04 |
| Mathematical Reasoning | -0.03 | 0.06 | -0.01 | 0.06 | 0.15 | 0.03 | -0.02 | 0.09 | -0.03 | -0.02 | 0.01 | -0.01 | -0.01 | -0.01 | 0.00 | -0.04 |
| Mathematics Knowledge | -0.06 | 0.08 | -0.02 | 0.12 | 0.25 | 0.04 | -0.04 | 0.14 | -0.05 | -0.06 | -0.02 | -0.01 | -0.01 | -0.01 | -0.02 | -0.09 |
| Mathematics Skills | -0.04 | 0.07 | -0.01 | 0.07 | 0.15 | 0.03 | -0.02 | 0.09 | -0.03 | -0.03 | 0.00 | -0.01 | -0.01 | -0.01 | 0.00 | -0.05 |
| Mathematics and Science | -0.02 | 0.07 | -0.00 | 0.05 | 0.17 | 0.02 | -0.01 | 0.12 | -0.01 | -0.02 | 0.01 | 0.00 | -0.01 | -0.00 | -0.00 | -0.03 |
| Mechanical | -0.03 | 0.11 | -0.02 | 0.16 | 0.03 | 0.07 | -0.00 | 0.03 | 0.02 | -0.07 | -0.06 | -0.01 | -0.01 | 0.01 | -0.01 | -0.08 |
| Medicine and Dentistry | -0.01 | 0.02 | 0.00 | 0.01 | 0.08 | 0.00 | -0.00 | 0.22 | -0.01 | -0.01 | 0.03 | 0.01 | -0.00 | -0.00 | 0.00 | -0.00 |
| Memorization | -0.04 | 0.04 | -0.01 | 0.04 | 0.17 | 0.02 | -0.02 | 0.10 | -0.02 | -0.03 | -0.00 | 0.00 | -0.02 | -0.01 | -0.01 | -0.05 |
| Memory | -0.04 | 0.04 | -0.01 | 0.04 | 0.17 | 0.02 | -0.02 | 0.10 | -0.02 | -0.03 | -0.00 | 0.00 | -0.02 | -0.01 | -0.01 | -0.05 |
| Monitoring | -0.07 | 0.12 | -0.02 | 0.08 | 0.32 | 0.03 | -0.03 | 0.21 | -0.04 | -0.06 | -0.02 | -0.00 | -0.03 | -0.02 | -0.01 | -0.08 |
| Multilimb Coordination | -0.05 | 0.09 | -0.03 | 0.07 | 0.03 | 0.03 | -0.01 | 0.06 | 0.01 | -0.07 | -0.06 | -0.01 | -0.02 | -0.00 | 0.00 | -0.08 |
| Near Vision | -0.09 | 0.09 | -0.03 | 0.10 | 0.27 | 0.03 | -0.04 | 0.20 | -0.04 | -0.08 | -0.04 | -0.01 | -0.04 | -0.03 | -0.02 | -0.12 |
| Negotiation | -0.05 | 0.08 | -0.01 | 0.05 | 0.20 | 0.01 | -0.02 | 0.13 | -0.02 | -0.03 | 0.00 | 0.00 | -0.02 | -0.02 | -0.01 | -0.06 |
| Night Vision | -0.00 | 0.03 | -0.01 | 0.02 | 0.00 | 0.01 | -0.00 | 0.00 | 0.01 | -0.01 | -0.00 | 0.00 | -0.01 | 0.00 | 0.02 | -0.01 |
| Number Facility | -0.04 | 0.07 | -0.01 | 0.06 | 0.14 | 0.02 | -0.02 | 0.09 | -0.03 | -0.03 | 0.00 | -0.01 | -0.01 | -0.01 | -0.00 | -0.05 |
| Operation Monitoring | -0.03 | 0.09 | -0.02 | 0.07 | 0.05 | 0.03 | -0.01 | 0.07 | -0.01 | -0.07 | -0.05 | -0.01 | -0.02 | -0.00 | 0.00 | -0.06 |
| Operation and Control | -0.02 | 0.10 | -0.02 | 0.06 | 0.01 | 0.03 | -0.01 | 0.04 | 0.00 | -0.06 | -0.05 | -0.01 | -0.01 | -0.00 | 0.01 | -0.06 |
| Operations Analysis | -0.01 | 0.06 | 0.00 | 0.04 | 0.08 | 0.03 | 0.00 | 0.07 | -0.03 | -0.01 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | -0.01 |
| Oral Comprehension | -0.10 | 0.14 | -0.03 | 0.10 | 0.39 | 0.03 | -0.05 | 0.26 | -0.05 | -0.07 | -0.01 | -0.01 | -0.04 | -0.03 | -0.02 | -0.13 |
| Oral Expression | -0.10 | 0.14 | -0.02 | 0.09 | 0.41 | 0.03 | -0.04 | 0.26 | -0.05 | -0.07 | -0.01 | -0.00 | -0.04 | -0.03 | -0.02 | -0.12 |
| Originality | -0.05 | 0.08 | -0.01 | 0.07 | 0.27 | 0.03 | -0.01 | 0.14 | -0.04 | -0.03 | 0.00 | 0.00 | -0.01 | -0.01 | -0.01 | -0.05 |
| Perceptual Abilities | -0.04 | 0.07 | -0.01 | 0.06 | 0.16 | 0.02 | -0.02 | 0.12 | -0.03 | -0.05 | -0.02 | -0.01 | -0.03 | -0.01 | -0.01 | -0.06 |
| Perceptual Speed | -0.05 | 0.07 | -0.02 | 0.06 | 0.15 | 0.02 | -0.03 | 0.12 | -0.02 | -0.06 | -0.04 | -0.01 | -0.03 | -0.01 | -0.00 | -0.07 |
| Peripheral Vision | -0.00 | 0.04 | -0.01 | 0.02 | 0.00 | 0.01 | -0.00 | 0.01 | 0.01 | -0.01 | -0.01 | 0.00 | -0.01 | -0.00 | 0.02 | -0.01 |
| Persistence | -0.16 | 0.20 | -0.06 | 0.17 | 0.62 | 0.04 | -0.07 | 0.39 | -0.08 | -0.15 | -0.06 | -0.01 | -0.07 | -0.05 | -0.05 | -0.22 |
| Personnel and Human Resources | -0.03 | 0.10 | -0.01 | 0.04 | 0.13 | 0.01 | -0.01 | 0.08 | -0.01 | -0.02 | 0.00 | -0.00 | -0.02 | -0.01 | -0.01 | -0.04 |
| Persuasion | -0.06 | 0.10 | -0.01 | 0.05 | 0.22 | 0.02 | -0.02 | 0.15 | -0.03 | -0.03 | 0.00 | 0.00 | -0.03 | -0.02 | -0.01 | -0.07 |
| Philosophy and Theology | -0.01 | 0.01 | 0.00 | 0.01 | 0.17 | 0.00 | 0.00 | 0.10 | -0.00 | -0.00 | 0.01 | 0.01 | -0.00 | -0.00 | -0.00 | -0.01 |
| Physical Strength | -0.03 | 0.05 | -0.02 | 0.05 | 0.04 | 0.01 | -0.01 | 0.06 | 0.00 | -0.04 | -0.04 | -0.01 | -0.02 | -0.00 | -0.01 | -0.05 |
| Physics | -0.01 | 0.05 | -0.00 | 0.08 | 0.05 | 0.04 | -0.00 | 0.04 | 0.00 | -0.01 | 0.00 | -0.00 | 0.00 | 0.00 | 0.00 | -0.02 |
| Practical Intelligence | -0.13 | 0.18 | -0.04 | 0.18 | 0.57 | 0.05 | -0.06 | 0.37 | -0.09 | -0.11 | -0.04 | -0.01 | -0.05 | -0.03 | -0.03 | -0.17 |
| Problem Sensitivity | -0.07 | 0.13 | -0.02 | 0.10 | 0.32 | 0.04 | -0.03 | 0.25 | -0.04 | -0.06 | -0.01 | -0.00 | -0.04 | -0.02 | -0.01 | -0.09 |
| Production and Processing | -0.04 | 0.08 | -0.02 | 0.05 | 0.04 | 0.01 | -0.01 | 0.03 | -0.01 | -0.07 | -0.07 | -0.02 | -0.01 | -0.00 | -0.03 | -0.06 |
| Programming | -0.00 | 0.01 | 0.00 | 0.01 | 0.02 | 0.00 | -0.01 | 0.01 | -0.05 | -0.00 | 0.00 | -0.00 | -0.00 | -0.00 | 0.00 | -0.01 |
| Psychology | -0.03 | 0.06 | 0.00 | 0.04 | 0.34 | 0.01 | -0.00 | 0.28 | -0.01 | -0.01 | 0.03 | 0.02 | -0.02 | -0.01 | 0.00 | -0.03 |
| Psychomotor Abilities | -0.04 | 0.07 | -0.02 | 0.06 | 0.03 | 0.02 | -0.01 | 0.05 | 0.00 | -0.06 | -0.05 | -0.01 | -0.02 | -0.00 | 0.00 | -0.06 |
| Public Safety and Security | -0.05 | 0.07 | -0.03 | 0.09 | 0.15 | 0.03 | -0.01 | 0.10 | -0.01 | -0.03 | -0.01 | -0.01 | -0.06 | -0.01 | 0.00 | -0.07 |
| Quality Control Analysis | -0.03 | 0.09 | -0.01 | 0.09 | 0.06 | 0.04 | -0.01 | 0.07 | -0.02 | -0.05 | -0.04 | -0.01 | -0.01 | -0.00 | -0.00 | -0.05 |
| Quantitative Abilities | -0.04 | 0.06 | -0.01 | 0.06 | 0.14 | 0.02 | -0.02 | 0.09 | -0.03 | -0.03 | 0.00 | -0.01 | -0.01 | -0.01 | 0.00 | -0.05 |
| Rate Control | -0.01 | 0.06 | -0.01 | 0.03 | 0.00 | 0.01 | -0.00 | 0.01 | 0.01 | -0.05 | -0.05 | -0.01 | -0.01 | -0.00 | 0.02 | -0.04 |
| Reaction Time | -0.02 | 0.09 | -0.01 | 0.06 | 0.02 | 0.03 | -0.00 | 0.04 | 0.01 | -0.06 | -0.05 | -0.00 | -0.02 | -0.00 | 0.02 | -0.05 |
| Reaction Time and Speed Abilities | -0.02 | 0.06 | -0.01 | 0.05 | 0.02 | 0.02 | -0.00 | 0.03 | 0.01 | -0.04 | -0.04 | -0.01 | -0.01 | -0.00 | 0.01 | -0.04 |
| Reading Comprehension | -0.07 | 0.10 | -0.01 | 0.07 | 0.34 | 0.02 | -0.04 | 0.22 | -0.05 | -0.06 | -0.00 | 0.00 | -0.03 | -0.03 | -0.01 | -0.08 |
| Reasoning Abilities | -0.06 | 0.10 | -0.01 | 0.08 | 0.28 | 0.03 | -0.03 | 0.19 | -0.04 | -0.05 | -0.01 | -0.00 | -0.03 | -0.02 | -0.01 | -0.08 |
| Repairing | -0.01 | 0.04 | -0.01 | 0.07 | 0.00 | 0.05 | 0.00 | 0.00 | 0.01 | -0.03 | -0.03 | -0.00 | -0.00 | 0.00 | 0.00 | -0.03 |
| Resource Management Skills | -0.03 | 0.10 | -0.01 | 0.05 | 0.13 | 0.02 | -0.01 | 0.09 | -0.02 | -0.02 | -0.00 | -0.00 | -0.01 | -0.01 | -0.00 | -0.04 |
| Response Orientation | -0.02 | 0.06 | -0.01 | 0.04 | 0.02 | 0.02 | -0.00 | 0.04 | 0.01 | -0.04 | -0.03 | -0.00 | -0.02 | -0.00 | 0.03 | -0.04 |
| Sales and Marketing | -0.06 | 0.07 | -0.02 | 0.03 | 0.08 | 0.01 | -0.01 | 0.04 | -0.02 | -0.02 | 0.01 | -0.02 | -0.01 | -0.01 | -0.01 | -0.07 |
| Science | -0.00 | 0.05 | 0.01 | 0.03 | 0.06 | 0.02 | 0.00 | 0.10 | -0.01 | 0.00 | 0.03 | 0.01 | 0.01 | 0.00 | 0.00 | 0.00 |
| Selective Attention | -0.06 | 0.09 | -0.02 | 0.07 | 0.21 | 0.02 | -0.03 | 0.14 | -0.03 | -0.06 | -0.04 | -0.01 | -0.04 | -0.02 | -0.01 | -0.08 |
| Self Control | -0.23 | 0.20 | -0.09 | 0.17 | 0.69 | 0.04 | -0.09 | 0.47 | -0.08 | -0.17 | -0.07 | -0.03 | -0.10 | -0.06 | -0.05 | -0.29 |
| Sensory Abilities | -0.04 | 0.07 | -0.02 | 0.05 | 0.12 | 0.02 | -0.01 | 0.09 | -0.01 | -0.04 | -0.02 | -0.00 | -0.02 | -0.01 | 0.00 | -0.06 |
| Service Orientation | -0.08 | 0.08 | -0.02 | 0.06 | 0.27 | 0.02 | -0.03 | 0.20 | -0.03 | -0.04 | 0.01 | -0.01 | -0.03 | -0.02 | -0.01 | -0.08 |
| Social Influence | -0.14 | 0.22 | -0.05 | 0.20 | 0.62 | 0.05 | -0.06 | 0.38 | -0.06 | -0.12 | -0.05 | -0.01 | -0.07 | -0.04 | -0.05 | -0.19 |
| Social Orientation | -0.18 | 0.13 | -0.06 | 0.12 | 0.61 | 0.02 | -0.07 | 0.42 | -0.05 | -0.12 | -0.05 | -0.01 | -0.07 | -0.05 | -0.05 | -0.21 |
| Social Perceptiveness | -0.07 | 0.10 | -0.02 | 0.06 | 0.32 | 0.01 | -0.03 | 0.22 | -0.03 | -0.05 | -0.00 | 0.00 | -0.03 | -0.02 | -0.01 | -0.08 |
| Social Skills | -0.06 | 0.10 | -0.01 | 0.06 | 0.27 | 0.02 | -0.02 | 0.18 | -0.03 | -0.04 | -0.00 | -0.00 | -0.03 | -0.02 | -0.01 | -0.07 |
| Sociology and Anthropology | -0.01 | 0.02 | 0.01 | 0.01 | 0.23 | 0.00 | 0.00 | 0.14 | -0.01 | -0.00 | 0.02 | 0.01 | -0.01 | -0.01 | -0.00 | -0.01 |
| Sound Localization | -0.00 | 0.03 | -0.01 | 0.02 | 0.01 | 0.01 | -0.00 | 0.00 | 0.01 | -0.01 | -0.01 | 0.00 | -0.01 | 0.00 | 0.02 | -0.01 |
| Spatial Abilities | -0.03 | 0.07 | -0.01 | 0.07 | 0.08 | 0.03 | -0.01 | 0.06 | -0.01 | -0.03 | -0.02 | -0.00 | -0.01 | -0.00 | 0.01 | -0.04 |
| Spatial Orientation | -0.01 | 0.05 | -0.01 | 0.04 | 0.01 | 0.02 | -0.00 | 0.01 | 0.01 | -0.01 | -0.01 | 0.00 | -0.01 | 0.00 | 0.03 | -0.02 |
| Speaking | -0.08 | 0.12 | -0.02 | 0.07 | 0.35 | 0.02 | -0.04 | 0.21 | -0.04 | -0.05 | -0.01 | -0.00 | -0.04 | -0.03 | -0.01 | -0.09 |
| Speech Clarity | -0.08 | 0.09 | -0.02 | 0.06 | 0.35 | 0.02 | -0.03 | 0.21 | -0.04 | -0.06 | -0.01 | -0.00 | -0.04 | -0.03 | -0.02 | -0.10 |
| Speech Recognition | -0.09 | 0.09 | -0.03 | 0.07 | 0.32 | 0.01 | -0.04 | 0.20 | -0.04 | -0.06 | -0.01 | -0.01 | -0.04 | -0.03 | -0.02 | -0.11 |
| Speed of Closure | -0.03 | 0.06 | -0.01 | 0.05 | 0.15 | 0.02 | -0.01 | 0.11 | -0.02 | -0.03 | -0.01 | -0.00 | -0.02 | -0.01 | -0.00 | -0.04 |
| Speed of Limb Movement | -0.02 | 0.04 | -0.01 | 0.04 | 0.02 | 0.01 | -0.00 | 0.03 | 0.01 | -0.03 | -0.03 | -0.00 | -0.02 | 0.00 | 0.00 | -0.04 |
| Stamina | -0.04 | 0.05 | -0.02 | 0.05 | 0.05 | 0.01 | -0.01 | 0.07 | 0.00 | -0.04 | -0.04 | -0.01 | -0.02 | -0.00 | -0.02 | -0.06 |
| Static Strength | -0.04 | 0.08 | -0.03 | 0.06 | 0.04 | 0.02 | -0.01 | 0.08 | 0.01 | -0.07 | -0.05 | -0.01 | -0.03 | -0.00 | -0.02 | -0.07 |
| Strength and Flexibility | -0.03 | 0.05 | -0.02 | 0.05 | 0.04 | 0.01 | -0.01 | 0.05 | 0.00 | -0.04 | -0.03 | -0.01 | -0.02 | -0.00 | -0.01 | -0.05 |
| Stress Tolerance | -0.21 | 0.17 | -0.08 | 0.15 | 0.65 | 0.04 | -0.08 | 0.46 | -0.08 | -0.16 | -0.06 | -0.02 | -0.09 | -0.06 | -0.06 | -0.27 |
| Systems Analysis | -0.03 | 0.07 | -0.00 | 0.06 | 0.18 | 0.03 | -0.01 | 0.11 | -0.04 | -0.02 | 0.01 | 0.00 | -0.01 | -0.01 | -0.01 | -0.04 |
| Systems Evaluation | -0.03 | 0.07 | -0.00 | 0.06 | 0.20 | 0.03 | -0.01 | 0.12 | -0.04 | -0.02 | 0.01 | 0.00 | -0.01 | -0.01 | -0.00 | -0.04 |
| Systems Skills | -0.04 | 0.08 | -0.01 | 0.07 | 0.22 | 0.03 | -0.01 | 0.14 | -0.04 | -0.03 | 0.00 | 0.00 | -0.01 | -0.01 | -0.01 | -0.05 |
| Technical Skills | -0.01 | 0.05 | -0.01 | 0.06 | 0.03 | 0.03 | -0.00 | 0.03 | -0.01 | -0.03 | -0.02 | -0.00 | -0.01 | 0.00 | 0.00 | -0.03 |
| Technology Design | -0.01 | 0.01 | 0.00 | 0.03 | 0.04 | 0.01 | -0.00 | 0.03 | -0.02 | -0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | -0.01 |
| Telecommunications | -0.02 | 0.04 | -0.00 | 0.04 | 0.06 | 0.04 | -0.01 | 0.04 | -0.03 | 0.00 | 0.01 | -0.00 | -0.02 | -0.01 | 0.00 | -0.02 |
| Therapy and Counselling | -0.01 | 0.01 | 0.01 | 0.01 | 0.21 | 0.00 | -0.00 | 0.20 | -0.00 | -0.00 | 0.03 | 0.02 | -0.01 | -0.01 | -0.00 | -0.00 |
| Time Management | -0.06 | 0.12 | -0.02 | 0.07 | 0.26 | 0.02 | -0.03 | 0.16 | -0.03 | -0.05 | -0.01 | -0.01 | -0.03 | -0.02 | -0.01 | -0.08 |
| Time Sharing | -0.05 | 0.08 | -0.02 | 0.06 | 0.18 | 0.02 | -0.02 | 0.12 | -0.01 | -0.04 | -0.02 | -0.01 | -0.03 | -0.01 | 0.00 | -0.07 |
| Transportation | -0.03 | 0.06 | -0.03 | 0.03 | 0.06 | 0.01 | -0.01 | 0.03 | -0.00 | -0.03 | -0.00 | -0.01 | -0.02 | -0.01 | 0.02 | -0.06 |
| Troubleshooting | -0.01 | 0.06 | -0.01 | 0.08 | 0.02 | 0.05 | -0.01 | 0.03 | -0.01 | -0.04 | -0.03 | -0.01 | -0.01 | 0.00 | 0.00 | -0.04 |
| Trunk Strength | -0.06 | 0.07 | -0.03 | 0.07 | 0.11 | 0.02 | -0.01 | 0.09 | 0.00 | -0.07 | -0.06 | -0.01 | -0.03 | -0.00 | -0.03 | -0.09 |
| Verbal Abilities | -0.08 | 0.12 | -0.02 | 0.08 | 0.37 | 0.03 | -0.04 | 0.23 | -0.05 | -0.06 | -0.01 | -0.00 | -0.04 | -0.03 | -0.02 | -0.10 |
| Visual Abilities | -0.03 | 0.07 | -0.02 | 0.06 | 0.09 | 0.02 | -0.01 | 0.07 | -0.01 | -0.04 | -0.02 | -0.01 | -0.02 | -0.01 | 0.01 | -0.05 |
| Visual Color Discrimination | -0.04 | 0.06 | -0.02 | 0.08 | 0.11 | 0.04 | -0.01 | 0.10 | -0.01 | -0.04 | -0.02 | -0.01 | -0.02 | -0.01 | -0.01 | -0.06 |
| Visualization | -0.05 | 0.09 | -0.02 | 0.11 | 0.15 | 0.04 | -0.01 | 0.11 | -0.02 | -0.05 | -0.03 | -0.01 | -0.02 | -0.00 | -0.00 | -0.07 |
| Wrist-Finger Speed | -0.02 | 0.04 | -0.01 | 0.04 | 0.01 | 0.01 | -0.00 | 0.02 | 0.00 | -0.03 | -0.03 | -0.01 | -0.01 | -0.00 | 0.00 | -0.04 |
| Writing | -0.05 | 0.09 | -0.01 | 0.05 | 0.31 | 0.02 | -0.03 | 0.18 | -0.04 | -0.04 | 0.01 | 0.00 | -0.03 | -0.02 | -0.01 | -0.07 |
| Written Comprehension | -0.07 | 0.10 | -0.01 | 0.07 | 0.34 | 0.03 | -0.04 | 0.22 | -0.05 | -0.06 | -0.01 | -0.00 | -0.03 | -0.03 | -0.01 | -0.09 |
| Written Expression | -0.05 | 0.09 | -0.01 | 0.06 | 0.33 | 0.02 | -0.03 | 0.20 | -0.04 | -0.04 | 0.00 | 0.00 | -0.03 | -0.02 | -0.01 | -0.07 |
In the table above, we can see the composition of skills shortages and surpluses within each industry in Australia.
Most notably, in the Education sector there are significant skills shortages in:
With similar skills shortages in Human Health & Social Work.
Conversely, there were moderate skills surpluses across Accomodation and Construction in:
Australia has been the lucky country for as long as I've been alive. However, it's easy to get complacent and lose touch with technological and global trends that are significantly impacting employment and equality outcomes.
Australia's unemployment is enviable on a global scale, however there are large systemic gaps between younger and older generations and men and women, especially when compared to our siblings in New Zealand.
Australia faces a large skills gap in 21st century technology and soft skills with surpluses in operations and manufacturing (20th Century Skills). It's clear Australia cannot rely on manufacturing and mining going forward
The industries most in need of upsklling in Australia are Education and Human Health & Social Work. With the largest skills surpluses being in Wholesale and Retail trade, Accomodation and Manufacturing.
This has been a very high level look into trends in employment and skill shortages. With more time, we may want to:
And after all....maybe it's not too late to save the lucky country after!